machine learning

Learn how the Citrine Platform accelerated reformulation of a chassis of cleansing products, reducing ingredient costs, and enabling consistency across new geographies.

Data-driven models are central to scientific discovery. In efforts to achieve state-of-the-art model accuracy, researchers are employing increasingly complex machine learning algorithms that often outperform simple regressions in interpolative settings (e.g. random k-fold cross-validation) but suffer from poor extrapolation performance, portability, and human interpretability, which limits their potential for facilitating novel scientific insight. Here we […]

Accurate uncertainty estimates can significantly improve the performance of iterative design of experiments, as in sequential and reinforcement learning. For many such problems in engineering and the physical sciences, the design task depends on multiple correlated model outputs as objectives and/or constraints. To better solve these problems, we propose a recalibrated bootstrap method to generate […]

The predictive capabilities of machine learning (ML) models used in materials discovery are typically measured using simple statistics such as the root-mean-square error (RMSE) or the coefficient of determination (r2) between ML-predicted materials property values and their known values. A tempting assumption is that models with low error should be effective at guiding materials discovery, […]

Read how the Citrine Platform was used to develop new carbon fiber process additives with local ingredients in record time.

Learn how Citrine’s AI Platform was used to rapidly screen 2500+ polymers in just 5 months. See how a new workflow was developed where researchers can now set a target and immediately receive a list of the top 10 polymers most likely to hit the target. 

Companies are thinking through the build versus buy decision on Materials Informatics platforms. This blog outlines what to think about.

Corrosion is an electrochemical phenomenon. It can occur via different modes of attack, each having its own mechanisms, and therefore there are multiple metrics for evaluating corrosion resistance. In corrosion resistant alloys (CRAs), the rate of localized corrosion can exceed that of uniform corrosion by orders of magnitude. Therefore, instead of uniform corrosion rate, more […]

Hear from Erin Antono as she describes what she likes about working at Citrine.

Materials innovation is essential to sustainability. Materials Informatics can accelerate that. To speed up adoption of MI we need both education and public research to produce FAIR data.